TIPS: Mining Top-K Locations to Minimize User-Inconvenience for Trajectory-Aware Services

TL;DR

This paper introduces the TIPS problem for optimally placing facilities to minimize user inconvenience for mobile users, proposing heuristics and validating them on real urban networks.

Contribution

It formulates the novel TIPS problem considering user trajectories and proposes efficient heuristics for two variants, MAXTIPS and AVGTIPS.

Findings

Heuristics effectively reduce user inconvenience in real networks.

Both TIPS variants are NP-hard, requiring heuristic solutions.

Empirical results demonstrate the efficiency of proposed heuristics.

Abstract

Facility location problems aim to identify the best locations to set up new services. Majority of the existing works typically assume that the users are static. However, there exists a wide array of services such as fuel stations, ATMs, food joints, etc., that are widely accessed by mobile users besides the static ones. Such trajectory-aware services should, therefore, factor in the trajectories of its users rather than simply their static locations. In this work, we introduce the problem of optimal placement of facility locations for such trajectory-aware services that minimize the user inconvenience. The inconvenience of a user is the extra distance traveled by her from her regular path to avail a service. We call this the TIPS problem (Trajectory-aware Inconvenience-minimizing Placement of Services) and consider two variants of it. The goal of the first variant, MAXTIPS, is to minimize the maximum inconvenience faced by any user, while that of the second, AVGTIPS, is to minimize the average inconvenience over all the users. We show that both these problems are NP-hard, and propose multiple efficient heuristics to solve them. Empirical evaluation on real urban-scale road networks validate the efficiency and effectiveness of the proposed heuristics.